Daniluk Paweł, Oleniecki Tymoteusz, Lesyng Bogdan
Bioinformatics Laboratory, Mossakowski Medical Research Centre, Polish Academy of Sciences, 02-106 Warsaw, Poland.
College of Inter-Faculty Individual Studies in Mathematics and Natural Sciences, University of Warsaw, 02-089 Warsaw, Poland.
Bioinformatics. 2021 Dec 22;38(1):80-85. doi: 10.1093/bioinformatics/btab571.
The well-known fact that protein structures are more conserved than their sequences forms the basis of several areas of computational structural biology. Methods based on the structure analysis provide more complete information on residue conservation in evolutionary processes. This is crucial for the determination of evolutionary relationships between proteins and for the identification of recurrent structural patterns present in biomolecules involved in similar functions. However, algorithmic structural alignment is much more difficult than multiple sequence alignment. This study is devoted to the development and applications of DAMA-a novel effective environment capable to compute and analyze multiple structure alignments.
DAMA is based on local structural similarities, using local 3D structure descriptors and thus accounts for nearest-neighbor molecular environments of aligned residues. It is constrained neither by protein topology nor by its global structure. DAMA is an extension of our previous study (DEDAL) which demonstrated the applicability of local descriptors to pairwise alignment problems. Since the multiple alignment problem is NP-complete, an effective heuristic approach has been developed without imposing any artificial constraints. The alignment algorithm searches for the largest, consistent ensemble of similar descriptors. The new method is capable to capture most of the biologically significant similarities present in canonical test sets and is discriminatory enough to prevent the emergence of larger, but meaningless, solutions. Tests performed on the test sets, including protein kinases, demonstrate DAMA's capability of identifying equivalent residues, which should be very useful in discovering the biological nature of proteins similarity. Performance profiles show the advantage of DAMA over other methods, in particular when using a strict similarity measure QC, which is the ratio of correctly aligned columns, and when applying the methods to more difficult cases.
DAMA is available online at http://dworkowa.imdik.pan.pl/EP/DAMA. Linux binaries of the software are available upon request.
Supplementary data are available at Bioinformatics online.
蛋白质结构比其序列更保守这一众所周知的事实构成了计算结构生物学多个领域的基础。基于结构分析的方法能提供关于进化过程中残基保守性更完整的信息。这对于确定蛋白质之间的进化关系以及识别参与相似功能的生物分子中存在的重复结构模式至关重要。然而，算法结构比对比多序列比对困难得多。本研究致力于开发和应用DAMA——一种能够计算和分析多个结构比对的新型有效环境。
DAMA基于局部结构相似性，使用局部三维结构描述符，因此考虑了比对残基的最近邻分子环境。它既不受蛋白质拓扑结构的限制，也不受其整体结构的限制。DAMA是我们之前研究（DEDAL）的扩展，该研究证明了局部描述符在成对比对问题中的适用性。由于多比对问题是NP完全问题，因此开发了一种有效的启发式方法，且不施加任何人为约束。比对算法搜索最大的、一致的相似描述符集合。新方法能够捕捉标准测试集中存在的大多数生物学上显著的相似性，并且具有足够的区分性以防止出现更大但无意义的解决方案。在包括蛋白激酶在内的测试集上进行的测试表明，DAMA能够识别等效残基，这在发现蛋白质相似性的生物学本质方面应该非常有用。性能概况显示了DAMA相对于其他方法的优势，特别是在使用严格的相似性度量QC（正确比对列的比率）时，以及在将这些方法应用于更困难的情况时。
DAMA可在http://dworkowa.imdik.pan.pl/EP/DAMA在线获取。可根据请求提供该软件的Linux二进制文件。
补充数据可在《生物信息学》在线获取。
